ABSTRACT COVID-19 is caused by a suspected zoonotic source of Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2). While coronaviruses (CoVs) are relatively common, mutations can cause severe symptoms in humans; the challenges of SARS-CoV-2 are: the long incubation period (2-14 days, median 5.1 days), high viral titer which can appear while a COVID-19+ patient is asymptomatic, and the long period of time in which it is viable outside of its host, both airborne and on surfaces. It is estimated as of May 28, 2020, that there are over 5.7 million cases in 212 countries. Symptoms can range from mild to severe and may include: fever, coughing, shortness of breath, sore throat, fatigue, congestion, and chills. Of those cases, 13.8% require medical interventions, with 6% of patients dying Tragically, there are no available vaccines against SARS-CoV-2. With a wide range of clinical symptoms and more importantly a large population of asymptomatic COVID-19+ patients, a crucial question regarding genetic susceptibility, i.e. whether human leukocyte antigens (HLA) play a role in the patient symptomology. Preliminary in-silico data have revealed binding affinity of specific HLAs to SARS- CoV-2 antigens, indicating a genetic HLA association with COVID-19 clinical symptoms, which is the primary objective of this application. We hypothesize that ?A certain HLA allele or combination of certain alleles can serve as biomarker for the severity of COVID-19?. To test this hypothesis, we propose to define HLA binding epitopes from dominant SARS-CoV-2 T cell antigens using in-silico analysis (Aim 1), determine the HLA alleles of symptomatic and asymptomatic of COVID-19 patients using whole genome genotyping (Aim 2), and examine the T cell function in correlation with HLA-associated disease protection and susceptibility (Aim 3). The results are expected to provide a broader understanding of the genetic HLA association pertaining to the severity of COVID-19. Additionally, results should provide critical measures in performing HLA typing and virus detection to identify high risk individuals. Utilizing this finding, we may be able to prevent transmission and mitigate the impact of this disease in our dental, health care personnel, and other front-line professionals who are particularly susceptible to aerosol or droplet virus transmission.